Sampling and convergence in free energy calculations of protein-ligand interactions: The binding of triphenoxypyridine derivatives to factor Xa and trypsin

The binding of a set of 10 triphenoxypyridine derivatives to two serine proteases, factor Xa and trypsin, has been used to analyze factors related to sampling and convergence in free energy calculations based on molecular dynamics simulation techniques. The inhibitors investigated were initially proposed as part of the Critical Assessment of Techniques for Free Energy Evaluation (CATFEE) project for which no experimental results nor any assessment of the predictions submitted by various groups have ever been published. The inhibitors studied represent a severe challenge for explicit free energy calculations. The mutations from one compound to another involve up to 19 atoms, the creation and annihilation of net charge and several alternate binding modes. Nevertheless, we demonstrate that it is possible to obtain highly converged results (+/- 5-10 kJ/mol) even for such complex multi-atom mutations by simulating on a nanosecond time scale. This is achieved by using soft-core potentials to facilitate the creation and deletion of atoms and by a careful choice of mutation pathway. The results show that given modest computational resources, explicit free energy calculations can be successfully applied to realistic problems in drug design.     

Investigation of cation-pi interactions in biological systems

Noncovalent interactions, such as van der Waals interactions, hydrogen bonds, salt bridge and cation-Pi interactions play extremely important roles in biological systems and, in contrast to covalent bonds, many such noncovalent interactions are not well understood. In the present work a new protocol has been developed to measure the enhancement of binding energies due to cation-Pi interactions between aromatic amino acids and organic or metal ions. Investigation of the cation-Pi interactions will provide further insight into the structure and function of biological molecules.     

Excited-state calculations with TD-DFT: from benchmarks to simulations in complex environments

In this perspective, we present an overview of recent progress on Time-Dependent Density Functional Theory (TD-DFT) with a specific focus on its accuracy and on models able to take into account environmental effects, including complex media. To this end, we first summarise recent benchmarks and define an average TD-DFT accuracy in reproducing excitation energies when a conventional approach is used. Next, coupling of TD-DFT with models able to account for different kinds of interactions between a central chromophore and nearby chemical objects (solvent, organic cage, metal as well as semi-conducting surface) is investigated. Examples of application to excitation properties are presented, allowing to briefly describe several recent computational strategies. In addition, an extension of TD-DFT to describe a phenomenon involving interacting chromophores, e.g. the electronic energy transfer (EET), is presented to illustrate that this methodology can be applied to processes beyond the vertical excitation. This perspective therefore aims to provide to non-specialists a flavour of recent trends in the field of simulations of excited states in "realistic" situations.     

On the cooperativity of cation-pi and hydrogen bonding interactions

Quantum chemical calculations are performed to gauge the effect of cation-pi and hydrogen bonding interactions on each other. M-phenol-acceptor (M = Li (+) and Mg (2+); acceptor = H(2)O, HCOOH, HCN, CH(3)OH, HCONH(2) and NH(3)) is taken as a model ternary system that exhibits the cation-pi and hydrogen bonding interactions. Cooperativity is quantified and the computed positive cooperativity between cation-pi and hydrogen bonding interactions is rationalized through reduced variational space (RVS) and charge analyses.     

Interplay between cation-pi, anion-pi and pi-pi interactions.

The interplay between three important noncovalent interactions involving aromatic rings is studied by means of high level ab initio calculations. They demonstrate that very strong synergic effects are present in complexes where either cation–π or anion–π and π‐‐π interactions coexist. These strong synergic effects have been studied using the “atoms in molecules” theory and the physical nature of the interactions investigated by means of the molecular interaction potential with polarization (MIPp).     

Steered molecular dynamics simulations of protein-ligand interactions

Molecular recognition and specific protein-ligandinteractions are central to many biochemical processes,such as enzyme catalysis, assembly of organelles, en-ergy transduction, signaling, diverse control functions,and replication, expression and storage of the geneticmaterial[1]. Moreover, protein-ligand interactions pro-vide the mechanism of many drug therapies and un-derstanding of such interactions is thus significant forrational drug design[1,2]. For the experimental studiesof protein-ligan…     

Orientation and alkylation effects on cation-pi interactions in aqueous solution

We have investigated the orientation dependence of the cation-pi interaction between a phenyl ring and a pyridinium ring in the context of a flexible model system in water. Of the four possible positions of the pyridinium nitrogen, ipso, ortho, meta, and para, we found a variation in the interaction energy of about 0.75 kcal mol(-1), with the stacking of the ipso-pyridinium ring providing the strongest interaction. The observed stability is attributed to the maximization of the electrostatic interaction, minimization of rotamers, and possible differences in hydration phenomena arising from alkylation.     

Statistical potential for modeling and ranking of protein-ligand interactions

Applications in structural biology and medicinal chemistry require protein-ligand scoring functions for two distinct tasks: (i) ranking different poses of a small molecule in a protein binding site and (ii) ranking different small molecules by their complementarity to a protein site. Using probability theory, we developed two atomic distance-dependent statistical scoring functions: PoseScore was optimized for recognizing native binding geometries of ligands from other poses and RankScore was optimized for distinguishing ligands from nonbinding molecules. Both scores are based on a set of 8,885 crystallographic structures of protein-ligand complexes but differ in the values of three key parameters. Factors influencing the accuracy of scoring were investigated, including the maximal atomic distance and non-native ligand geometries used for scoring, as well as the use of protein models instead of crystallographic structures for training and testing the scoring function. For the test set of 19 targets, RankScore improved the ligand enrichment (logAUC) and early enrichment (EF(1)) scores computed by DOCK 3.6 for 13 and 14 targets, respectively. In addition, RankScore performed better at rescoring than each of seven other scoring functions tested. Accepting both the crystal structure and decoy geometries with all-atom root-mean-square errors of up to 2 ? from the crystal structure as correct binding poses, PoseScore gave the best score to a correct binding pose among 100 decoys for 88% of all cases in a benchmark set containing 100 protein-ligand complexes. PoseScore accuracy is comparable to that of DrugScore(CSD) and ITScore/SE and superior to 12 other tested scoring functions. Therefore, RankScore can facilitate ligand discovery, by ranking complexes of the target with different small molecules; PoseScore can be used for protein-ligand complex structure prediction, by ranking different conformations of a given protein-ligand pair. The statistical potentials are available through the Integrative Modeling Platform (IMP) software package (http://salilab.org/imp) and the LigScore Web server (http://salilab.org/ligscore/).     

Mass spectrometry based tools to investigate protein-ligand interactions for drug discovery

The initial stages of drug discovery are increasingly reliant on development and improvement of analytical methods to investigate protein-protein and protein-ligand interactions. For over 20 years, mass spectrometry (MS) has been recognized as providing a fast, sensitive and high-throughput methodology for analysis of weak non-covalent complexes. Careful control of electrospray ionization conditions has enabled investigation of the structure, stability and interactions of proteins and peptides in a solvent free environment. This critical review covers the use of mass spectrometry for kinetic, dynamic and structural studies of proteins and protein complexes. We discuss how conjunction of mass spectrometry with related techniques and methodologies such as ion mobility, hydrogen-deuterium exchange (HDX), protein footprinting or chemical cross-linking can provide us with structural information useful for drug development. Along with other biophysical techniques, such as NMR or X-ray crystallography, mass spectrometry provides a powerful toolbox for investigation of biological problems of medical relevance (204 references).     

Scoring noncovalent protein-ligand interactions: A continuous differentiable function tuned to compute binding affinities

Summary Exploitation of protein structures for potential drug leads by molecular docking is critically dependent on methods for scoring putative protein-ligand interactions. An ideal function for scoring must exhibit predictive accuracy and high computational speed, and must be tolerant of variations in the relative protein-ligand molecular alignment and conformation. This paper describes the development of an empirically derived scoring function, based on the binding affinities of protein-ligand complexes coupled with their crystallographically determined structures. The function's primary terms involve hydrophobic and polar complementarity, with additional terms for entropic and solvation effects. The issue of alignment/conformation dependence was solved by constructing a continuous differentiable nonlinear function with the requirement that maxima in ligand conformation/alignment space corresponded closely to crystallographically determined structures. The expected error in the predicted affinity based on cross-validation was 1.0 log unit. The function is sufficiently fast and accurate to serve as the objective function of a molecular-docking search engine. The function is particularly well suited to the docking problem, since it has spatially narrow maxima that are broadly accessible via gradient descent.     

Free-energy calculations of the host–guest association in grafted supramolecular assemblies

Herein, we investigate the impact of grafting macrocyclic hosts with hydrophobic cavities onto a gold surface on the association with a guest molecule of particular importance to applications for molecular machines. We establish that the increase of the grafted alkyl chain length and number of anchor points strengthens the binding of the guest with the β-cyclodextrin host. This is the opposite effect with the p-sulfonatocalix[4]arene host for which the grafting considerably reduces the strength of the host–guest association. The structural and thermodynamic characterizations, carried out with free energy simulations, are combined to rationalize the differences in the association process in both heterogeneous and homogeneous conditions.     

Metal ligand aromatic cation-pi interactions in metalloproteins: ligands coordinated to metal interact with aromatic residues

Cation-pi interactions between aromatic residues and cationic amino groups in side chains and have been recognized as noncovalent bonding interactions relevant for molecular recognition and for stabilization and definition of the native structure of proteins. We propose a novel type of cation-pi interaction in metalloproteins; namely interaction between ligands coordinated to a metal cation--which gain positive charge from the metal--and aromatic groups in amino acid side chains. Investigation of crystal structures of metalloproteins in the Protein Data Bank (PDB) has revealed that there exist quite a number of metalloproteins in which aromatic rings of phenylalanine, tyrosine, and tryptophan are situated close to a metal center interacting with coordinated ligands. Among these ligands are amino acids such as asparagine, aspartate, glutamate, histidine, and threonine, but also water and substrates like ethanol. These interactions play a role in the stability and conformation of metalloproteins, and in some cases may also be directly involved in the mechanism of enzymatic reactions, which occur at the metal center. For the enzyme superoxide dismutase, we used quantum chemical computation to calculate that Trp163 has an interaction energy of 10.09 kcal mol(-1) with the ligands coordinated to iron.     

Pyrogallarenes as alkali metal receptors: the role of cation-pi interactions in complexation

Crystallization studies of C-methyl pyrogallarene with potassium, rubidium and caesium bromides or chlorides resulted in a hydrogen bonded molecular cage in which the alkali metal cations are eta6 coordinated to aromatic rings via strong cation-pi interactions.